| Accurate predictions on small data with a tabular foundation model N Hollmann, S Müller, L Purucker, A Krishnakumar, M Körfer, SB Hoo, ... Nature 637 (8045), 319-326, 2025 | 600 | 2025 |
| TabArena: A Living Benchmark for Machine Learning on Tabular Data N Erickson, L Purucker, A Tschalzev, D Holzmüller, PM Desai, D Salinas, ... NeurIPS 2025 Datasets and Benchmarks Track, 2025 | 29 | 2025 |
| Efficient MedSAMs: Segment Anything in Medical Images on Laptop J Ma, F Li, S Kim, R Asakereh, BH Le, DK Nguyen-Vu, A Pfefferle, M Wei, ... arXiv preprint arXiv:2412.16085, 2024 | 22 | 2024 |
| Don't Waste Your Time: Early Stopping Cross-Validation E Bergman*, L Purucker*, F Hutter AutoML Conference 2024, 2024 | 20 | 2024 |
| The effect of random seeds for data splitting on recommendation accuracy L Wegmeth, T Vente, L Purucker, J Beel Perspectives on the Evaluation of Recommender Systems Workshop (PERSPECTIVES …, 2023 | 16 | 2023 |
| CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure L Purucker, J Beel International Conference on Automated Machine Learning, 1/1-23, 2023 | 12 | 2023 |
| Assembled-OpenML: Creating Efficient Benchmarks for Ensembles in AutoML with OpenML L Purucker, J Beel First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022 | 12 | 2022 |
| DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation AT Pfefferle, L Purucker, F Hutter CVPR 2024: Segment Anything In Medical Images On Laptop, 2024 | 11 | 2024 |
| Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML L Purucker, L Schneider, M Anastacio, J Beel, B Bischl, H Hoos International Conference on Automated Machine Learning, 10/1-34, 2023 | 11 | 2023 |
| OpenML: Insights from 10 years and more than a thousand papers B Bischl, G Casalicchio, T Das, M Feurer, S Fischer, P Gijsbers, ... Patterns, 2025 | 10* | 2025 |
| Unreflected Use of Tabular Data Repositories Can Undermine Research Quality A Tschalzev, L Purucker, S Lüdtke, F Hutter, C Bartelt, H Stuckenschmidt The Future of Machine Learning Data Practices and Repositories at ICLR 2025, 2025 | 10* | 2025 |
| Large Language Models Engineer Too Many Simple Features for Tabular Data J Küken, L Purucker, F Hutter NeurIPS 2024 Third Table Representation Learning Workshop, 2024 | 10 | 2024 |
| Transfer Learning for Finetuning Large Language Models T Strangmann, L Purucker, JKH Franke, I Rapant, F Ferreira, F Hutter NeurIPS 2024 Workshop on Adaptive Foundation Models, 2024 | 7 | 2024 |
| Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data A Garg, M Ali, N Hollmann, L Purucker, S Müller, F Hutter 1st ICML Workshop on Foundation Models for Structured Data, 2025 | 6 | 2025 |
| AMLTK: A Modular AutoML Toolkit in Python E Bergman, M Feurer, A Bahram, AR Balef, L Purucker, S Segel, ... Journal of Open Source Software 9 (100), 6367, 2024 | 6 | 2024 |
| Towards Benchmarking Foundation Models for Tabular Data With Text M Mráz, B Das, A Gupta, L Purucker, F Hutter 1st ICML Workshop on Foundation Models for Structured Data, 2025 | 5* | 2025 |
| HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models RS Sukthanker, A Zela, B Staffler, A Klein, L Purucker, JKH Franke, ... NeurIPS 2024 Datasets and Benchmarks Track, 2024 | 5 | 2024 |
| Advancing biogeographical ancestry predictions through machine learning CS Heinzel, L Purucker, F Hutter, P Pfaffelhuber Forensic Science International: Genetics, 2025 | 4 | 2025 |
| Ensembling Finetuned Language Models for Text Classification SP Arango, M Janowski, L Purucker, A Zela, F Hutter, J Grabocka NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles …, 2024 | 4 | 2024 |
| Early Stopping Tabular In-Context Learning J Küken, L Purucker, F Hutter 1st ICML Workshop on Foundation Models for Structured Data, 2025 | 3 | 2025 |
Frank HutterPrior Labs; ELLIS Institute Tübingen; University of FreiburgVerified email at cs.uni-freiburg.de
